barplot(sample(10:15, 8, replace = TRUE), col = 1:8, names.arg = 1:8)

head(colors(), n = 20)

barplot(sample(10:15, 8, replace = TRUE), 
  col = colors()[sample(1:657, size = 8)])

graphBarplotCol <- function(n){
  myX <- rnorm(n)
  myY <- rnorm(n)
  myCol <- c(2, 3, 4, sample(2:4, size = (n - 3), replace = TRUE))
  myYCut <- cut(myY, breaks = -4:4)
  myXCut <- cut(myX, breaks = -4:4)
  myYCutCol <- table(myCol, myYCut)
  myXCutCol <- table(myCol, myXCut)
  rColX <- myXCutCol[1,] / (myXCutCol[1,] + myXCutCol[2,] + 
                              myXCutCol[3,])
  gColX <- myXCutCol[2,] / (myXCutCol[1,] + myXCutCol[2,] + 
                              myXCutCol[3,])
  bColX <- myXCutCol[3,] / (myXCutCol[1,] + myXCutCol[2,] + 
                              myXCutCol[3,])
  rColX[is.na(rColX)] <- 0
  gColX[is.na(gColX)] <- 0
  bColX[is.na(bColX)] <- 0
  rColY <- myYCutCol[1,] / (myYCutCol[1,] + myYCutCol[2,] + 
                              myYCutCol[3,])
  gColY <- myYCutCol[2,] / (myYCutCol[1,] + myYCutCol[2,] + 
                              myYCutCol[3,])
  bColY <- myYCutCol[3,] / (myYCutCol[1,] + myYCutCol[2,] + 
                              myYCutCol[3,])
  rColY[is.na(rColY)] <- 0
  gColY[is.na(gColY)] <- 0
  bColY[is.na(bColY)] <- 0
  op <- par(no.readonly = TRUE)
  par(mar = c(2, 3, 1, 1))
  layout(matrix(c(1, 1, 0, 
                  2, 2, 3, 
                  2, 2, 3), ncol = 3, byrow = TRUE))
  barplot(table(myXCut), las = 1, col = rgb(rColX, gColX, bColX))
  plot(x = myX, y = myY, col = myCol, pch = 16, 
       xlim = c(-4, 4), ylim = c(-4, 4), cex = 1.5, 
       panel.first = grid())
  barplot(table(myYCut), las = 1, horiz = TRUE, 
          col = rgb(rColY, gColY, bColY))
  par(op)
}

boxplot(matrix(rnorm(1000), ncol = 10), main = "terrain.colors()", 
  col = terrain.colors(10), axes = FALSE)

boxplot(matrix(rnorm(1000), ncol = 10), main = "heat.colors()", 
  col = heat.colors(10), axes = FALSE)

boxplot(matrix(rnorm(1000), ncol = 10), main = "topo.colors()", 
  col = topo.colors(10), axes = FALSE)

boxplot(matrix(rnorm(1000), ncol = 10), main = "cm.colors()", 
  col = cm.colors(10), axes = FALSE)

boxplot(matrix(rnorm(1000), ncol = 10), main = "rainbow()", 
  col = rainbow(10), axes = FALSE)

boxplot(matrix(rnorm(2500), ncol = 25), 
  col = colorRampPalette(c('blue', 'red'))(25), axes = FALSE)

boxplot(matrix(rnorm(2500), ncol = 25), 
  col = colorRampPalette(c('blue', 'white', 'red'))(25), 
  axes = FALSE)

boxplot(matrix(rnorm(2500), ncol = 25), 
  col =  colorRampPalette(c(
    rgb(255, 136, 0, maxColorValue = 255),  
    rgb(0, 94, 255, maxColorValue = 255)))(25), 
  axes = FALSE)

pkgCheck <- function(x){ 
    if (!require(x, character.only = TRUE)){
        install.packages(x, dependencies = TRUE)
        if(!require(x, character.only = TRUE)) {
            stop()
        }
    }
}
pkgCheck("palettesForR")

showPalette(Echo_gpl)

showPalette(GrayViolet_gpl)

groupTest <- sample(1:3, size = 100, replace = TRUE) 
valueTest <- sample(1:7, size = 100, replace = TRUE)
tableTest <- table(groupTest, valueTest)
print(tableTest)

barplot(tableTest, 
  col = Echo_gpl, axes = FALSE, beside = TRUE)

groupTest <- sample(1:3, size = 100, replace = TRUE) 
valueTest <- sample(1:7, size = 100, replace = TRUE)
tableTest <- table(valueTest, groupTest)
print(tableTest)

barplot(tableTest, 
  col = Echo_gpl[c(1, 4, 7, 10, 13, 16, 19)], 
  axes = FALSE, beside = TRUE)

makeImpact <- function(myPal, numP = 300, impact = 0.33, multCex = 3){
  myX <- sample(0:1000, size = numP, replace = TRUE)/1000
  myY <- sample(0:1000, size = numP, replace = TRUE)/1000
  distImpact <- sqrt((myX - impact)^2 + (myY - impact)^2)
  dfXY <- data.frame(myX, myY, distImpact)
  plot(x = dfXY$myX, y = dfXY$myY, axes = FALSE, 
    xlab = "", ylab = "", cex = dfXY$distImpact*multCex, 
    col = myPal, pch = 16)
}

par(mfrow = c (1, 2), mar = c(0, 0, 0, 0))
makeImpact(myPal = Echo_gpl, numP = 3000, impact = 0.33)
makeImpact(myPal = Dark_gpl, numP = 3000, impact = 0.66)

par(mfrow = c (1, 2), mar = c(0, 0, 0, 0))
makeImpact(myPal = Coldfire_gpl, numP = 3000, impact = 0.33)
makeImpact(myPal = Blues_gpl, numP = 3000, impact = 0.66)

pkgCheck <- function(x){ 
    if (!require(x, character.only = TRUE)){
        install.packages(x, dependencies = TRUE)
        if(!require(x, character.only = TRUE)) {
            stop()
        }
    }
}
pkgCheck("RColorBrewer")

display.brewer.all()

boxplot(matrix(rnorm(1000), ncol = 10), 
  col = brewer.pal(10, "Paired"), axes = FALSE)

pkgCheck("cranlogs") # devtools::install_github("metacran/cranlogs")
getVerDate <- function(myPkg, startY){
    pkgURL <- sprintf('https://cran.r-project.org/src/contrib/Archive/%s/', myPkg)
    contURL <- readLines(pkgURL)
    vecCont <- contURL[grep(contURL, 
        pattern = '(<tr><td valign=\"top\"><img src=\"/icons/compressed.gif\")')]
    vecContSplit <- strsplit(vecCont, split = ">|<")
    pkgVersion <- sapply(vecContSplit, "[[", 13)
    pkgVersion <- sapply(strsplit(pkgVersion, split = "(tar.gz)|_"), "[[", 2)
    pkgDate <- sapply(strsplit(sapply(vecContSplit, "[[", 19), 
        split = " "), "[[", 1)
    vPkg <- data.frame(date = pkgDate, ver = pkgVersion)
    vPkg <- vPkg[as.Date(vPkg$date, 
        format = "%Y-%m-%d") > as.Date(paste0(startY, "-01-01"), 
        format = "%Y-%m-%d"),]
    downl <- cran_downloads(from = paste0(startY, "-01-01"), 
        to = format(Sys.time(), "%Y-%m-%d"), packages = myPkg)
    downl <- downl[as.Date(downl$date, 
        format = "%Y-%m-%d") > as.Date(paste0(startY, "-01-01"), 
        format = "%Y-%m-%d"),]
    return(list(vPkg, downl))
}
getImports <- function(myPkg) { ### a changer pour avoir les reverse dependencies (x3)
    pkgURL <- sprintf('https://cran.r-project.org/web/packages/%s/', myPkg)
    contURL <- readLines(pkgURL)
    vecCont <- contURL[grep(contURL, 
        pattern = '(<td>Imports:</td>)') + 1]
    vecContSplit <- strsplit(vecCont, split = ">|<")[[1]]
    vecContSplit <- strsplit(vecContSplit[grep(vecContSplit, 
        pattern = '^(a href=)')], split = "/")
    Imports <- sapply(vecContSplit, "[[", 2)
    jj <- intersect(c("Depends", "Imports", "Suggests"), colnames(dcf))
    val <- unlist(strsplit(dcf[, jj], ","), use.names=FALSE)
    val <- gsub("\\s.*", "", trimws(val))
    val[val != "R"]
}
dataD <- getVerDate(myPkg = "ggplot2", startY = 2006)
vPkg <- dataD[[1]]
downl <- dataD[[2]]
plot(x = downl$date, y = cumsum(downl$count), type = "l", 
    xlab = "Time", ylab = "Cumulative number of downloads", panel.first = grid())
points(x = as.Date(vPkg$date, format = "%Y-%m-%d"), 
    y = cumsum(downl$count)[as.Date(downl$date, format = "%Y-%m-%d") %in% 
    as.Date(vPkg$date, format = "%Y-%m-%d")], pch = 16)
yy <- sum(downl$count)
xx <- Sys.Date()
abline(h = yy, v = xx)
text(
  x = as.Date("2012-01-01", format = "%Y-%m-%d"), 
  y = yy, 
  labels = paste0("Downloads = ", yy), 
  pos = 1, cex = 3)

pkgCheck <- function(x){ 
    if (!require(x, character.only = TRUE)){
        install.packages(x, dependencies = TRUE)
        if(!require(x, character.only = TRUE)) {
            stop()
        }
    }
}
pkgCheck("ggplot2")

# ggplot(data = <DATA>) + 
#   <GEOM_FUNCTION>(
#      mapping = aes(<MAPPINGS>),
#      stat = <STAT>, 
#      position = <POSITION>
#   )

data(iris)
plot(x = iris$Sepal.Length, y = iris$Sepal.Width, 
  main = "base", pch = 16)

data(iris)
p <- ggplot(data = iris, aes(x = Sepal.Length, y = Sepal.Width))
p + geom_point() + ggtitle("ggplot2")

plot(x = iris$Sepal.Length, y = iris$Sepal.Width, 
  main = "base", pch = 16, col = iris$Species)

p <- ggplot(data = iris, 
  aes(x = Sepal.Length, y = Sepal.Width, colour = Species))
p + geom_point() + ggtitle("ggplot2")

op <- par(no.readonly = TRUE)
par(mar = c(4, 4, 2, 8))
plot(x = iris$Sepal.Length, y = iris$Sepal.Width, 
  axes = FALSE, pch = 16, col = iris$Species, 
  panel.first = {
    rect(par("usr")[1], 
      par("usr")[3], 
      par("usr")[2], 
      par("usr")[4], 
      col = "lightgray",  border = NA)
    abline(v = 4:8, col = "white", lwd = 2, lty = 1)
    abline(h = 2:5, col = "white", lwd = 2, lty = 1)
    grid(col = "white", lwd = 1, lty = 1)
  })
title("base", adj = 0, line = 0.5)
axis(1, col = NA, col.ticks = 1, cex.axis = 0.9)
axis(2, col = NA, col.ticks = 1, las = 1, cex.axis = 0.9)
par(xpd = TRUE)
legend(8.2, 3.5, legend = levels(iris$Species), bty = "n", 
  pch = 16, col = as.numeric(unique(iris$Species)), 
  title = "Species")
par(op)

# linear regressions
lmFits <- lapply(1:3, function(i){
  fitSp1 <- lm(iris$Sepal.Width[as.numeric(iris$Species) == i] ~ 
    iris$Sepal.Length[as.numeric(iris$Species) == i])
  fStat1 <- summary(fitSp1)$fstatistic
  rSq1 <- summary(fitSp1)$r.squared
  pVal1 <- summary(fitSp1)$coefficients[2, 4]
  stat1 <- paste0("F=", round(fStat1[1], digits = 2), 
    "; DF=", fStat1[2], "/", fStat1[3], "; r-sq=", round(rSq1, digits = 2), 
    "; p-val=", round(pVal1, digits = 6))
  return(list(fitSp1, stat1))
})

p <- ggplot(data = iris, 
  aes(x = Sepal.Length, y = Sepal.Width, colour = Species))
p <- p + geom_point() + 
  ggtitle("ggplot2") + 
  stat_smooth(method = "lm", se = FALSE)

p <- p + annotate(geom = "text", x = 6, y = 2.250, label = lmFits[[1]][[2]], colour = 2)
p <- p + annotate(geom = "text", x = 6, y = 2.125, label = lmFits[[2]][[2]], colour = 3)
p + annotate(geom = "text", x = 6, y = 2.000, label = lmFits[[3]][[2]], colour = 4)

plot(x = iris$Sepal.Length, y = iris$Sepal.Width, 
  main = "base", pch = 16, col = iris$Species)
abline(lmFits[[1]][[1]], col = 1)
abline(lmFits[[2]][[1]], col = 2)
abline(lmFits[[3]][[1]], col = 3)

plot(x = iris$Sepal.Length, y = iris$Sepal.Width, 
  main = "base", pch = 16, col = iris$Species)
abline(lmFits[[1]][[1]], col = 1)
abline(lmFits[[2]][[1]], col = 2)
abline(lmFits[[3]][[1]], col = 3)
text(x = 5.5, y = 2.3, labels = lmFits[[1]][[2]], pos = 4)
text(x = 5.5, y = 2.15, labels = lmFits[[2]][[2]], pos = 4, col = 2)
text(x = 5.5, y = 2.0, labels = lmFits[[3]][[2]], pos = 4, col = 3)

op <- par(no.readonly = TRUE)
par(mar = c(4, 4, 2, 8))
plot(x = iris$Sepal.Length, y = iris$Sepal.Width, 
  axes = FALSE, pch = 16, col = iris$Species, 
  panel.first = {
    rect(par("usr")[1], 
      par("usr")[3], 
      par("usr")[2], 
      par("usr")[4], 
      col = "lightgray",  border = NA)
    abline(v = 4:8, col = "white", lwd = 2, lty = 1)
    abline(h = 2:5, col = "white", lwd = 2, lty = 1)
    grid(col = "white", lwd = 1, lty = 1)
  })
title("base", adj = 0, line = 0.5)
axis(1, col = NA, col.ticks = 1, cex.axis = 0.9)
axis(2, col = NA, col.ticks = 1, las = 1, cex.axis = 0.9)
clip(min(iris$Sepal.Length[iris$Species == "setosa"]), 
     max(iris$Sepal.Length[iris$Species == "setosa"]), 
     min(iris$Sepal.Width), max(iris$Sepal.Width))
abline(lmFits[[1]][[1]], col = 1, lwd = 2)
clip(min(iris$Sepal.Length[iris$Species == "versicolor"]), 
     max(iris$Sepal.Length[iris$Species == "versicolor"]), 
     min(iris$Sepal.Width), max(iris$Sepal.Width))
abline(lmFits[[2]][[1]], col = 2, lwd = 2)
clip(min(iris$Sepal.Length[iris$Species == "virginica"]), 
     max(iris$Sepal.Length[iris$Species == "virginica"]), 
     min(iris$Sepal.Width), max(iris$Sepal.Width))
abline(lmFits[[3]][[1]], col = 3, lwd = 2)
clip(min(iris$Sepal.Length), max(iris$Sepal.Length), 
     min(iris$Sepal.Width), max(iris$Sepal.Width))
text(x = 5.5, y = 2.35, labels = lmFits[[1]][[2]], pos = 4)
text(x = 5.5, y = 2.2, labels = lmFits[[2]][[2]], pos = 4, col = 2)
text(x = 5.5, y = 2.05, labels = lmFits[[3]][[2]], pos = 4, col = 3)
par(xpd = TRUE)
legend(8.2, 3.5, legend = levels(iris$Species), bty = "n", 
  pch = 16, col = as.numeric(unique(iris$Species)), 
  title = "Species")
par(op)

pkgCheck <- function(x){ 
    if (!require(x, character.only = TRUE)){
        install.packages(x, dependencies = TRUE)
        if(!require(x, character.only = TRUE)) {
            stop()
        }
    }
}
pkgCheck("plotly")
pkgCheck("gapminder")